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Detection of Prostate Cancer using Recurrent Neural Network
Subject area: Science,Engineering and Technology · Area of research: Machine Learning
Abstract
Prostate cancer is a type of cancer that affects men, and it usually starts in the prostate gland, a small organ in the male reproductive system. It's one of the most common cancers in men. In U.S, prostate cancer affects men more frequently than any other type of cancer. The clinical presentation of prostate cancer is often asymptomatic in its early stages, leading to delayed diagnosis. Symptoms may include urinary problems, sexual dysfunction, and, in advanced cases, bone pain. Early detection relies on screening methods, primarily the prostate-specific antigen (PSA) test and digital rectal examination (DRE). These tools, despite some controversies, remain integral in identifying potential cases for further evaluation. Prostate cancer is more common in older men, typically over the age of 50. If your family has a history of prostate cancer, you might be at a higher risk. It can also be more common in certain ethnic groups. Early detection may be an important tool in getting appropriate and timely treatment, and that?s what our problem statement is. For Detection we can use different algorithm like CNN by getting MRI image form of data or RNN for CSV data. Here we?ve chosen RNN algorithm for detection of prostate cancer. We will train, test and validate our data and give the final accuracy which will tell how suitable this model is in terms of prostate cancer detection.
Keywords
Neural Network, Prediction, Gleason Score, Prostate Cancer, RNN.
How to cite this paper
@article{1705472,
author = {Shraddha Singh, Ajay Sharma, Mithilesh Vishwakarma, Dr. S. K Singh},
title = {Detection of Prostate Cancer using Recurrent Neural Network},
journal = {Iconic Research And Engineering Journals},
year = {2024},
volume = {7},
number = {8},
pages = {93-97},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1705472.pdf},
abstract = {Prostate cancer is a type of cancer that affects men, and it usually starts in the prostate gland, a small organ in the male reproductive system. It's one of the most common cancers in men. In U.S, prostate cancer affects men more frequently than any other type of cancer. The clinical presentation of prostate cancer is often asymptomatic in its early stages, leading to delayed diagnosis. Symptoms may include urinary problems, sexual dysfunction, and, in advanced cases, bone pain. Early detection relies on screening methods, primarily the prostate-specific antigen (PSA) test and digital rectal examination (DRE). These tools, despite some controversies, remain integral in identifying potential cases for further evaluation. Prostate cancer is more common in older men, typically over the age of 50. If your family has a history of prostate cancer, you might be at a higher risk. It can also be more common in certain ethnic groups. Early detection may be an important tool in getting appropriate and timely treatment, and that?s what our problem statement is. For Detection we can use different algorithm like CNN by getting MRI image form of data or RNN for CSV data. Here we?ve chosen RNN algorithm for detection of prostate cancer. We will train, test and validate our data and give the final accuracy which will tell how suitable this model is in terms of prostate cancer detection.},
keywords = {Neural Network, Prediction, Gleason Score, Prostate Cancer, RNN.},
month = {February},
}